System and method for automatic language model selection

Abstract

A system and method for generating a transcript of an audio input. An embodiment of a system and method may include generating a phonetic lattice by decoding the audio input and producing a transcription based on the phonetic lattice and based on a first language model. A transcription may be analyzed to produce analysis results. Analysis results may be used to select from a plurality of language models, one language model and the selected language model may be used to generate a transcript of the audio input.

The invention claimed is: 
     
       1. A computer-implemented method of generating a transcript of an audio input, the method comprising:
 generating a phonetic lattice by decoding the audio input; 
 producing a transcription based on the phonetic lattice and based on a first language model; 
 associating words identified in the transcription with a certainty value calculated for each identified word; 
 including words associated with a certainty value higher than a first threshold value in a combined index; 
 selecting, from a plurality of language models and based on the combined index, a second language model; and 
 generating a second transcription of the audio input based on the phonetic lattice and using the second language model. 
 
     
     
       2. The method of  claim 1 , wherein the first language model is a general model and the second language model is a specific language model. 
     
     
       3. The method of  claim 1 , comprising:
 combining at least two sub-words identified in the transcription to produce a word and including the produced word in the combined index. 
 
     
     
       4. The method of  claim 1 , comprising identifying key phrases in the transcription and including the key phrases in the combined index. 
     
     
       5. The method of  claim 1 , comprising, selecting the second language model based on calculating a plurality of match values by relating a respective plurality of specific language models to the combined index and selecting the specific language model associated with the highest match value. 
     
     
       6. The method of  claim 1 , comprising:
 associating sub-words identified in the transcription with a certainty value calculated for each identified sub-word; 
 identifying a sequence of sub-words associated with a certainty value higher than a second threshold value; 
 producing a word based on the identified sequence of sub-words; and 
 including the produced word in the combined index. 
 
     
     
       7. A computer-implemented method of generating a transcript of an audio input, the method comprising:
 producing a first transcription of the audio input using a first language model; 
 associating words identified in the first transcription with a certainty value calculated for each identified word; 
 including words associated with a certainty value higher than a first threshold value in a structured data; 
 selecting, from a plurality of language models, a second language model by matching the plurality of language models with the structured data; and 
 producing a second transcription of the audio input using the second language model. 
 
     
     
       8. An article comprising a non-transitory computer-readable storage medium, having stored thereon instructions that, when executed by a controller, cause the controller to:
 generate a phonetic lattice by decoding the audio input; 
 produce a transcription based on the phonetic lattice and based on a first language model; 
 associate words identified in the transcription with a certainty value calculated for each identified word; 
 include words associated with a certainty value higher than a first threshold value in a combined index; 
 select, from a plurality of language models and based on the combined index, a second language model; and 
 use the second language model and the phonetic lattice to generate a second transcript of the audio input. 
 
     
     
       9. The article of  claim 8 , wherein the first language model is a general model and the second language model is a specific language model. 
     
     
       10. The article of  claim 8 , wherein the instructions when executed further result in:
 combining at least two sub-words identified in the transcription to produce a word and including the produced word in the combined index. 
 
     
     
       11. The article of  claim 8 , wherein the instructions when executed further result in identifying key phrases in the transcription and including the key phrases in the combined index. 
     
     
       12. The article of  claim 8 , wherein the instructions when executed further result in selecting the second language model based on calculating a plurality of match values by relating a respective plurality of specific language models to the combined index and selecting the specific language model associated with the highest match value. 
     
     
       13. The article of  claim 8 , wherein the instructions when executed further result in:
 associating sub-words identified in the transcription with a certainty value calculated for each identified sub-word; 
 identifying a sequence of sub-words associated with a certainty value higher than a second threshold value; 
 producing a word based on the identified sequence of sub-words; and 
 including the produced word in the combined index.